Prompt @engineerrprompt
Creator of localGPT | Building something cool! Generative AI, Tech, Arts, Life! youtube.com/@engineerprompt Joined July 2023-
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If you are looking for end-to-end prototyping with llama3, make sure to checkout this session where I joined the amazing team @AIMakerspace to talk about dataset preparation, model fine-tuning and deployment. Really enjoyed the session. Session: youtube.com/watch?v=anIBtQ…
SLMs like Phi-3-mini are great for small specific tasks but are also great candidates for fine-tuning on your own datasets. Thanks to @UnslothAI, fine-tuning Phi-3-mini is really easy. Learn how to get started here: youtu.be/U5jU4YJodJo
Llama-3 8B with 1M Context. Can anyone run the benchmarks on it?
Phi-3-mini is a great model for its size but how good is it at RAG, query routing and agentic use? I put it to test in this video: youtu.be/_4hFNzY1iMA
Want to build an AI powered application but don't know where to start? Checkout this session. We will cover dataset creation, finetuning, and deployment of the model so the rest of the world can interact with your creation.
Want to build an AI powered application but don't know where to start? Checkout this session. We will cover dataset creation, finetuning, and deployment of the model so the rest of the world can interact with your creation.
Llama3 out of the box is more compliant with prompts compared to its predecessors. In this video I wanted to explore how uncensored the model is. Testing it via @GroqInc, @Meta and @perplexity_ai youtu.be/9oYGb6t-ybw
Groq API is the fastest inference speed on the market. The fabulous tutorial by @engineerrprompt explains how to get started with LLAMA-3 using the Groq API in your own applications. hubs.la/Q02tRZb40
LLAMA3 from @AIatMeta on @GroqInc is insanely fast. 800 tokens/sec on 8B and ~300 tokens/sec for 70B. Best part, you can use their API for free. Here is how to get started youtu.be/ySwJT3Z1MFI
AI stocks are the new meme stocks......
What's better than LLAMA3? Your own finetuned LLAMA3. Learn how to get started with finetuning using @UnslothAI (one of the best options if you are GPU poor like me :) ) youtu.be/aQmoog_s8HE
First look at llama3, really impressive beyond the benchmarks, the only thing I was hoping was more than 8k context and that 400B version looks on part with Claude Opus youtu.be/b2MPvE1OyHg
We got LLAMA-3!!!!
That was quick! The instruct version of Mixtral 8x22B from @MistralAI looks amazing.
That was quick! The instruct version of Mixtral 8x22B from @MistralAI looks amazing.
I tested the new Mixtral MoE from @MistralAI. For a base model, it's really impressive. Here is the video: youtu.be/VwbBBcvsWZM
If you are building RAG pipelines, you need to checkout ColBERTv2 (by @lateinteraction) as possible replacement to Dense Embeddings. RAGatouille by @bclavie is the easiest way to get started. Learn how to use it in @LangChainAI and @llama_index youtu.be/kEgeegk9iqo
OpenAI is finally open 😅
IAComunIA @IAcomunIA
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“I don’t give a shit about AGI. I want this technology to deliver on the promise it has made. And it has not.” —Nick Frosst, @cohere co-founder
A Whisper transcribing which takes just 326ms for a 60s audio clip! 🤯 Pair this with @GroqInc, and you'll have an assistant that finishes tasks faster than you can explain yourself in the next 60 seconds! Definitely check this out!
BOOM! Whisper + Speaker Diarisation! 🔥 Blazingly fast meeting transcription all with a simple call to an API - powered by Inference Endpoints ⚡ - Whisper to transcribe speech to text (w/ Flash Attention) - Diarization to break down the transcription by speakers (w/ Pyannote)…
ColBERT for the win! Great to see evaluations like this, super easy to represent ColBERT in @vespaengine "Our best performing method for handling RAG Retrieval on all datasets was ColBERT v2 with SentenceSplitter chunking." superlinked.com/vectorhub/arti…
PSA to not believe every AI thing you read online! My “100 quadrillion” parameters pic is spreading around the internet 🛜 Most of big AI news accounts have no idea what they are talking about
Billionaire Michael Bloomberg once boasted that the NYPD was his private army. Tonight, it’s the NetanYahu PD – dedicated to stamping out a righteous student protest against the worst war criminal of this century and his genocidal regime.
Police have broken into Hamilton Hall at Columbia University to arrest students inside who’ve taken it over last night in order to pressure the university to divest
AutoTrain isn't just about LLM finetuning. 8 Tasks supported excluding 5 different types of LLM finetuning 💥
dolphin-2.9-mixtral-8x22b is released! Compute sponsored by @CrusoeEnergy Trained by myself, @LucasAtkins7, @FernandoNetoAi FFT using Laser Scanner to selectively target 50% of the layers. Uncensored models obey! You are responsible for anything you generate with it.
Phi-3 notebook out! Finetune Phi 2x faster and use 50% less VRAM than HF+FA2 with @UnslothAI! Had to Mistral-fy it due to sliding window attention, & fixed the 2048/2047 SWA bug. Also unfused Attention & MLP, so some diff in QLoRA loss but 16bit the same. colab.research.google.com/drive/1NvkBmkH…
New ORPO Colab for Llama-3 8b is out! ORPO combines SFT & DPO into 1 step, so no more 2 step approach! Plus with @UnslothAI, finetuning is 2x faster, uses 80% less VRAM & 4x longer contexts are possible! Thanks to oKatanaaa & At&Dev for making this work! colab.research.google.com/drive/11t4njE3…
I published my filtered and uncensored dataset for Dolphin-2.9 on @huggingface so if you wanna make your own spin on Dolphin, or just see how Dolphin is created, you can check it out. Thanks to all the upstream dataset creators for open source data! huggingface.co/datasets/cogni…
Unsloth has surpassed 500K+ monthly model downloads on @huggingface! 🥳 🦥 Thanks for the support! 🩷 See our collection of 4bit models + more: huggingface.co/unsloth
New 🤖 agents video out using LangGraph (@LangChainAI) powered by Llama3 70B on @GroqInc to make an Email Agent youtu.be/lvQ96Ssesfk
A reminder that no one knows what they're doing in deep learning and why things work and that the best we can do is pray for our models to perform 🤣
Mozilla published a nice writeup on how llamafile helped them evaluate the quality of AI models and quantization formats. The writeup goes into detail on the code, costs, and has a heartwarming story on some history with the local LLaMA community. blog.mozilla.ai/local-llm-as-j…
It's been a week since LLaMA 3 dropped. In that time, we've: - extended context from 8K -> 128K - trained multiple ridiculously performant fine-tunes - got inference working at 800+ tokens/second If Meta keeps releasing OSS models, closed providers won't be able to compete.
🦙 Have you fine-tuned Llama 3 and built an end-to-end prototype yet? Come May 1 to see the entire end-to-end process with @huggingface tools! Our friend @engineerrprompt will join us for the walkthrough and Q&A! lu.ma/llmappshf
@winglian @Orwelian84 You can set RoPE config values under Advanced Configuration > Model Initialization: